Define the set of true null hypotheses, \(_{0}\lbrace (t,k):\, 1\le t<k\le K,\textrm { such that } \Omega ^*_{t,k} = 0\rbrace \) , as the set of indices \((t,k)\)  for which there is no edge between the nodes \(t\)  and \(k\) . To control the error incurred by multiple testing, we focus on the false discovery rate (FDR), which is the average number of Type I errors relative to the total number of discoveries [1]}. Recall that \(\tilde{\Omega }_{t,k}\)  is a consistent and asymptotically normal estimator of \(\Omega _{t,k}\) . We consider the natural test statistic \(\tilde{W}_{t,k}=n^{1/2}\tilde{\Omega }_{t,k}/\hat{s}_{tk}\)  for \(_{0;tk}\) , where \(\hat{s}^2_{tk}=\hat{\Omega }_{t,k}^2 + \hat{\Omega }_{t,t}\hat{\Omega }_{k,k}\) . Given a cutoff \(\tau >0\) , the total number of discoveries is
\(R_{\tau } := \sum _{1\le t < k \le K} [|\tilde{W}_{t,k}| > \tau ].\) 
